Workflow Templates

Automated workflow that generates custom AI image backgrounds from text prompts using Gemini's Nano Banana (native image generation), removes video backgrounds, and composites videos on AI-generated scenes. Create any background you can imagine without needing stock images. How it works • Describe background: Provide video URL and text prompt describing desired background scene (e.g., "modern office with city skyline at golden hour") • AI generates image: Gemini creates a background image from your prompt in ~10-20 seconds • Upload to Drive: Generated background is saved to Google Drive and made publicly accessible • Remove & composite: Video background is removed and composited on AI-generated scene with centered template • Save final video: Completed video is uploaded to Google Drive with shareable link Set up steps ⏱️ Total setup time: ~5 minutes • Get Gemini API Key (~1 min): Visit https://aistudio.google.com/apikey, create new API key, add to n8n Settings → Variables as GEMINI_KEY • Get VideoBGRemover API Key (~2 min): Visit https://videobgremover.com/n8n, sign up, add to n8n as VIDEOBGREMOVER_KEY • Connect Google Drive (~2 min): Click "Save Background Image to Drive" node, click "Connect", authorize n8n Use cases: Marketing videos with custom branded environments tailored to your message Product demos with unique AI-generated backgrounds that match your product aesthetic Social media content with creative scenes you can't find in stock libraries AI avatars placed in AI-generated worlds Presentations with custom backgrounds generated for specific topics A/B testing different background variations for the same video Pricing: Gemini: ~$0.03 per generated image VideoBGRemover: $0.50-$2.00 per minute of video Total: ~$0.53-$2.03 per video Triggers: Webhook (for automation) or Manual (for testing) Processing time: Typically 5-7 minutes total Prompt tips: Be descriptive and specific. Instead of "office," try: "A modern minimalist office with floor-to-ceiling windows overlooking a city skyline at golden hour. Warm sunlight, polished concrete floors, sleek wooden desks, green plants."

This AI-powered workflow transforms n8n workflow JSON files into publication-ready, SEO-optimized markdown posts for the n8n community. Simply upload your workflow's JSON, and let Google Gemini 2.5 Pro, guided by a LlamaIndex-powered knowledge base of best practices, automatically generate compelling content. Why Use This Workflow? Time Savings: Reduces the time to create a detailed workflow post from over an hour of manual writing to under 2 minutes. Cost Reduction: Eliminates the need for separate AI content subscriptions or outsourcing content creation tasks. Error Prevention: Enforces content quality and structural consistency by using a knowledge base of n8n's official guidelines, minimizing formatting errors. Ideal For n8n Workflow Creators:** To quickly document and share their creations on the community platform without the tedious, time-consuming writing process. Developer Advocates:** To standardize and accelerate the production of technical tutorials and workflow showcases. Content & Marketing Teams:** To streamline the content pipeline for n8n-related blog posts, tutorials, and community engagement initiatives. How It Works Trigger: The process starts when you upload an n8n workflow JSON file via a simple web form. Data Extraction: The workflow automatically extracts the JSON content from the uploaded file. Intelligence Layer: An advanced AI agent, powered by Google Gemini 2.5 Pro, analyzes the structure, nodes, and metadata of your workflow. Knowledge Retrieval: The agent consults a specialized, in-memory knowledge base built from n8n's content guidelines. This knowledge base is created by parsing documents with LlamaIndex and refined with a Cohere Reranker for maximum accuracy. Content Generation: The AI agent synthesizes the technical details from your JSON with the best practices from the knowledge base to write a complete, benefit-driven markdown post. Output & Delivery: The final, polished markdown content is generated as the workflow's output, ready to be copied and pasted into the n8n community platform. Setup Guide Prerequisites | Requirement | Type | Purpose | |-------------|------|---------| | n8n instance | Essential | Workflow execution platform | | Google Gemini API Key | Essential | Powers the core AI content generation | | LlamaIndex Cloud API Key | Essential | Parses documents for the knowledge base | | Cohere API Key | Optional | Improves knowledge base search results | | Google Drive Account | Optional | For automatically updating the knowledge base from a Google Doc | Installation Steps Import the JSON file to your n8n instance. Configure credentials: Google Gemini: In the "GEmini 2.5 pro" node, create and add your Google Gemini API credential. LlamaIndex: In the three HTTP Request nodes named "Parse Document...", "Monitor Document...", and "Retrieve Parsed...", create an HTTP Header Auth credential. The header name is Authorization and the value is Bearer YOUR_LLAMA_INDEX_API_KEY. Cohere: (Optional) In the "Reranker Cohere" node, create and add your Cohere API credential. Google Drive: (Optional) If you plan to auto-update the knowledge base, configure Google Drive OAuth2 credentials for the "Knowledge Base Updated Trigger" and "Download Knowledge Document" nodes. Update environment-specific values: To use the knowledge base auto-update feature, go to the "Knowledge Base Updated Trigger" node and select the Google Drive file containing your content guidelines. Customize settings: The primary system prompt in the "n8ncreator" agent node can be modified to adjust the tone, style, or structure of the generated content. Test execution: Run the workflow manually and use the form to upload a sample n8n workflow JSON file to verify that all connections work correctly. Technical Details Core Nodes | Node | Purpose | Key Configuration | |------|---------|-------------------| | Form Trigger | Initiates the workflow via a file upload. | Set the "Input Json Workflow" field to required. | | Langchain Agent | Orchestrates the entire content creation process. | The system prompt contains all instructions for the AI. | | ChatGoogleGemini | Provides the core generative AI capabilities. | Select your Gemini model of choice (e.g., gemini-2.5-pro). | | VectorStoreInMemory | Acts as the agent's knowledge base tool. | Configured to use embeddings from a Google Gemini model. | | HTTPRequest | Interacts with the LlamaIndex API to parse documents. | Set up with LlamaIndex API endpoint and authentication. | Customization Options Basic Adjustments: Change AI Model:** Replace the ChatGoogleGemini node with another LLM node (e.g., OpenAI, Anthropic) to use a different provider. Adjust System Prompt:** Modify the prompt in the "n8ncreator" node to tailor the output for different platforms (e.g., blog, internal wiki) or change the writing style. Advanced Enhancements: Automated Publishing:** Connect the output of the "n8ncreator" node to a Ghost, WordPress, or GitHub node to automatically publish the generated post. Add Web Search:** Equip the Langchain Agent with a web search tool to allow it to fetch live information about new n8n nodes or services. Batch Processing:** Replace the Form Trigger with a Read Binary Files node to process an entire folder of workflow JSON files in a single run. Performance & Optimization | Metric | Expected Performance | Optimization Tips | |--------|---------------------|-------------------| | Execution time | ~1 minute per run | Largely dependent on the Gemini API response time. | | API calls | 1 LLM call per post | Knowledge base updates trigger LlamaIndex/Google calls separately. | | Error handling | Built-in retry logic for document parsing | Add an error workflow path after the "n8ncreator" node to handle AI generation failures. | Troubleshooting Common Issues: | Problem | Cause | Solution | |---------|-------|----------| | AI output is generic or incomplete | The input JSON file is invalid or lacks key information (e.g., no node names). | Ensure you are uploading a valid, exported n8n workflow JSON. Verify the workflow has been saved with descriptive node names. | | LlamaIndex parsing fails | The LlamaIndex API key is incorrect or the source document is inaccessible. | Double-check your LlamaIndex API credential. Ensure the Google Doc sharing settings allow access. | | Credential Error | API keys are missing or incorrect for Gemini, LlamaIndex, or Cohere. | Go to the specified nodes and verify that the correct credentials have been created and selected. | Created by: khaisa Studio Category: AI Tags: AI, Content Generation, Google Gemini, LlamaIndex, Automation Need custom workflows? Contact us Connect with the creator: Portfolio • Workflows • LinkedIn • Medium • Threads

Who’s it for Teams who want to automatically generate structured meeting minutes from uploaded transcripts and instantly share them in Slack. Perfect for startups, project teams, or any company that collects meeting transcripts in Google Drive. How it works / What it does This workflow automatically turns raw meeting transcripts into well-structured minutes in Markdown and posts them to Slack: Google Drive Trigger – Watches a specific folder. Any new transcript file added will start the workflow. Download File – Grabs the transcript. Prep Transcript – Converts the file into plain text and passes the transcript downstream. Message a Model – Sends the transcript to OpenAI GPT for summarization using a structured system prompt (action items, decisions, N/A placeholders). Make Minutes – Formats GPT’s response into a Markdown file. Slack: Send a message – Posts a Slack message announcing the auto-generated minutes. Slack: Upload a file – Uploads the full Markdown minutes file into the chosen Slack channel. End result: your Slack channel always has clear, standardized minutes right after a meeting. How to set up Google Drive Create a folder where you’ll drop transcript files. Configure the folder ID in the Google Drive Trigger node. OpenAI Add your OpenAI API credentials in the Message a Model node. Select a supported GPT model (e.g., gpt-4o-mini or gpt-4). Slack Connect your Slack account and set the target channel ID in the Slack nodes. Run the workflow and drop a transcript file into Drive. Minutes will appear in Slack automatically. Requirements Google Drive account (for transcript upload) OpenAI API key (for text summarization) Slack workspace (for message posting and file upload) How to customize the workflow Change summary structure*: Adjust the system prompt inside *Message a Model (e.g., shorter summaries, language other than English). Different output format*: Modify *Make Minutes to output plain text, PDF, or HTML instead of Markdown. New destinations**: Add more nodes to send minutes to email, Notion, or Confluence in parallel. Multiple triggers**: Replace Google Drive trigger with Webhook if you want to integrate with Zoom or MS Teams transcript exports. Good to know OpenAI API calls are billed separately. See OpenAI pricing. Files must be text-based (.txt or .md). For PDFs or docs, add a conversion step before summarization. Slack requires the bot user to be a member of the target channel, otherwise you’ll see a not_in_channel error.

🐱 MemeCoin Art Generator - using Gemini Flash NanoBanana & upload to Twitter Automatically generates memecoin art and posts it to Twitter (X) powered by Google Gemini, NanoBanana image generation, and n8n automation. 🧩 Overview This workflow creates viral style memecoin images (like Popcat) and posts them directly to Twitter with a witty, Gen Z style tweet. It combines text to image AI, scheduled triggers, and social publishing, all in one seamless flow. Workflow flow: Define your memecoin mascot (name, description, and base image URL). Generate an AI image prompt and a meme tweet. Feed the base mascot image into Gemini Image Generation API. Render a futuristic memecoin artwork using NanoBanana. Upload the final image and tweet automatically to Twitter. 🧠 Workflow Diagram ⚙️ Key Components | Node | Function | |------|-----------| | Schedule Trigger | Runs automatically at chosen intervals to start meme generation. | | Define Memecoin | Defines mascot name, description, and base image URL. | | AI Agent | Generates tweet text and creative image prompt using Google Gemini. | | Google Gemini Chat Model | Provides trending topic context and meme phrasing. | | Get Source Image | Fetches the original mascot image (e.g., Popcat). | | Convert Source Image to Base64 | Prepares image for AI based remixing. | | Generate Image using NanoBanana | Sends the prompt and base image to Gemini Image API for art generation. | | Convert Base64 to PNG | Converts the AI output to an image file. | | Upload to Twitter | Uploads generated image to Twitter via media upload API. | | Create Tweet | Publishes the tweet with attached image. | 🪄 How It Works 1️⃣ Schedule Trigger - starts the automation (e.g., hourly or daily). 2️⃣ Define Memecoin - stores your mascot metadata: memecoin_name: popcat mascot_description: cat with open mouth mascot_image: https://i.pinimg.com/736x/9d/05/6b/9d056b5b97c0513a4fc9d9cd93304a05.jpg 3️⃣ AI Agent - prompts Gemini to: Write a short 100 character tweet in Gen Z slang. Create an image generation prompt inspired by current meme trends. 4️⃣ NanoBanana API - applies your base image + AI prompt to create art. 5️⃣ Upload & Tweet - final image gets uploaded and posted automatically. 🧠 Example Output Base Source Image: Generated Image (AI remix): Published Tweet: Example tweet text: > Popcat's about to go absolutely wild, gonna moon harder than my last test score! 🚀📈 We up! #Popcat #Memecoin 🧩 Setup Tutorial 1️⃣ Prerequisites | Tool | Purpose | |------|----------| | n8n (Cloud or Self hosted) | Workflow automation platform | | Google Gemini API Key | For generating tweet and image prompts | | Twitter (X) API OAuth1 + OAuth2 | For uploading and posting tweets | 2️⃣ Import the Workflow Download memecoin art generator.json. In n8n, click Import Workflow → From File. Set up and connect credentials: Google Gemini API Twitter OAuth (Optional) Adjust Schedule Trigger frequency to your desired posting interval. 3️⃣ Customize Your MemeCoin In the Define Memecoin node, edit these fields to change your meme theme: memecoin_name: "doggo" mascot_description: "shiba inu in astronaut suit" mascot_image: "https://example.com/shiba.jpg" That’s it - next cycle will generate your new meme and post it. 4️⃣ API Notes Gemini Image Generation API Docs:** https://ai.google.dev/gemini-api/docs/image-generation#gemini-image-editing API Key Portal:** https://aistudio.google.com/api-keys

Who is this for? This workflow is designed for online store owners, customer-success teams, and marketing operators who want to automatically verify customers' WhatsApp numbers and deliver order updates or invoice links via WhatsApp. It is built around WooCommerce order WooCommerce Trigger (order.updated) but is easily adaptable to Shopify or other platforms that provide billing and line_items in the WooCommerce Trigger payload. What this Workflow Does / Key Features Listens for WooCommerce order events (example: order.updated) via a Webhook or a WooCommerce trigger. Filters only orders with status "completed" and maps the payload into a normalized object: { data: { customer, products, invoice_link } } using the Code node Order Completed check. Iterates over line items using SplitInBatches to control throughput. Cleans phone numbers (Clean WhatsApp Number code node) by removing all non-digit characters. Verifies whether the cleaned phone number is registered on WhatsApp using Rapiwa's verify endpoint (POST https://app.rapiwa.com/api/verify-whatsapp). If verified, sends a templated WhatsApp message via Rapiwa (POST https://app.rapiwa.com/api/send-message). Appends an audit row to a "Verified & Sent" Google Sheet for successful sends, or to an "Unverified & Not Sent" sheet for unverified numbers. Uses Wait and batching to throttle requests and avoid API rate limits. Requirements HTTP Bearer credential for Rapiwa (example name in flow: Rapiwa Bearer Auth). WooCommerce API credential for the trigger (example: WooCommerce (get customer)) Running n8n instance with nodes: WooCommerce Trigger, Code, SplitInBatches, HTTP Request, IF, Google Sheets, Wait. Rapiwa account and a valid Bearer token. Google account with Sheets access and OAuth2 credentials configured in n8n. WooCommerce store (or any WooCommerce Trigger source) that provides billing and line_items in the payload. How to Use — step-by-step Setup 1) Credentials Rapiwa: Create an HTTP Bearer credential in n8n and paste your token (flow example name: Rapiwa Bearer Auth). Google Sheets: Add an OAuth2 credential (flow example name: Google Sheets). WooCommerce: Add the WooCommerce API credential or configure a Webhook on your store. 3) Configure Google Sheets The exported flow uses spreadsheet ID: 1S3RtGt5xxxxxxxXmQi_s (Sheet gid=0) as an example. Replace with your spreadsheet ID and sheet gid. Ensure your sheet column headers exactly match the mapping keys listed below (case and trailing spaces must match or be corrected in the mapping). 5) Verify HTTP Request nodes Verify endpoint: POST https://app.rapiwa.com/api/verify-whatsapp — sends { number } (uses HTTP Bearer credential). Send endpoint: POST https://app.rapiwa.com/api/send-message — sends number, message_type=text, and a templated message that uses fields from the Clean WhatsApp Number output. Google Sheet Column Structure The Google Sheets nodes in the flow append rows with these column keys. Make sure the spreadsheet headers A Google Sheet formatted like this ➤ sample | Name | Number | Email | Address | Product Title | Product ID | Total Price | Invoice Link | Delivery Status | Validity | Status | |----------------|---------------|-------------------|------------------------------------------|-----------------------------|------------|---------------|--------------------------------------------------------------------------------------------------------------|-----------------|------------|-----------| | Abdul Mannan | 8801322827799 | contact@spagreen.net | mirpur dohs | Air force 1 Fossil 1:1 - 44 | 238 | BDT 5500.00 | Invoice link | completed | verified | sent | | Abdul Mannan | 8801322827799 | contact@spagreen.net | mirpur dohs h#1168 rd#10 av#10 mirpur dohs dhaka | Air force 1 Fossil 1:1 - 44 | 238 | BDT 5500.00 | Invoice link | completed | unverified | not sent | Important Notes Do not hard-code API keys or tokens; always use n8n credentials. Google Sheets column header names must match the mapping keys used in the nodes. Trailing spaces are common accidental problems — trim them in the spreadsheet or adjust the mapping. The IF node in the exported flow compares to the string "true". If the verify endpoint returns boolean true/false, convert to string or boolean consistently before the IF. Message templates in the flow reference $('Clean WhatsApp Number').item.json.data.products[0] — update templates if you need multiple-product support. Useful Links Dashboard:** https://app.rapiwa.com Official Website:** https://rapiwa.com Documentation:** https://docs.rapiwa.com Support & Help WhatsApp**: Chat on WhatsApp Discord**: SpaGreen Community Facebook Group**: SpaGreen Support Website**: https://spagreen.net Developer Portfolio**: Codecanyon SpaGreen

## Podcast on Autopilot — Generate Podcast Ideas, Scripts & Audio Automatically with Eleven Labs, GPT-5 and Claude Sonnet 4.0 Bring your solo podcast to life — on full autopilot. This workflow uses GPT-5 and Claude Sonnet to turn a single topic input into a complete podcast episode intro and ready-to-send audio file. How it works Start a chat trigger – enter a seed idea or topic (e.g., “habits,” “failure,” “technology and purpose”). Podcast Idea Agent (GPT-5) instantly crafts a thought-provoking, Rogan- or Bartlett-style episode concept with a clear angle and takeaway. Podcast Script Agent (Claude 4.0 Sonnet) expands that idea into a natural, engaging 60-second opening monologue ready for recording. Text-to-Speech via ElevenLabs automatically converts the script into a high-quality voice track. Email automation sends the finished MP3 directly to your inbox. Perfect for • Solo creators who want to ideate, script and voice short podcasts effortlessly • Content teams prototyping daily or weekly audio snippets • Anyone testing AI-driven storytelling pipelines Customization tips • Swap ElevenLabs with your preferred TTS service by editing the HTTP Request node. • Adjust prompt styles for tone or audience in the Idea and Script Agents. • Modify the Gmail (or other mail service) node to send audio to any destination (Drive, Slack, Notion, etc.). • For reuse at scale, add variables for episode number, guest name, or theme category — just clone and update the trigger node. Watch step-by-step tutorial (how to build it yourself) https://www.youtube.com/watch?v=Dan3_W1JoqU Requirements & disclaimer • Requires API keys for OpenAI + Anthropic + ElevenLabs (or your chosen TTS). • You’re responsible for managing costs incurred through AI or TTS usage. • Avoid sharing sensitive or private data as input into prompt flows. • Designed with modularity so you can turn off or swap/deep-link any stage (idea → script → voice → email) without breaking the chain.

Automate video transcription and Q&A with async VLM processing that scales from short clips to long recordings. What this workflow does Monitors Google Drive for new files in a specific folder and grabs the file ID on create Automatically downloads the binary to hand off for processing Sends the video to VLM Run for async transcription with a callback URL that posts results back to n8n Receives the transcript JSON via Webhook and appends a row in Google Sheets with the video identifier and transcript data Enables chat Q&A through the Chat Trigger + AI Agent. The agent fetches relevant rows from Sheets and answers only from those segments using the connected chat model Setup Prerequisites: Google Drive and Google Sheets accounts, VLM Run API credentials, OpenAI (or another supported) chat model credentials, n8n instance. Install the verified VLM Run node by searching for VLM Run in the nodes list, then click Install. You can also confirm on npm if needed. After install, it integrates directly for robust async transcription. Quick Setup: Google Drive folder watch Add Google Drive Trigger and choose Specific folder. Set polling to every minute, event to File Created. Connect Drive OAuth2. Download the new file Add Google Drive node with Download. Map {{$json.id}} and save the binary as data. Async transcription with VLM Run Add VLM Run node. Operation: video. Domain: video.transcription. Enable Process Asynchronously and set Callback URL to your Webhook path (for example /transcript-video). Add your VLM Run API key. Webhook to receive results Add Webhook node with method POST and path /transcript-video. This is the endpoint VLM Run calls when the job completes. Use When Last Node Finishes or respond via a Respond node if you prefer. Append to Google Sheets Add Google Sheets node with Append. Point to your spreadsheet and sheet. Map: Video Name → the video identifier from the webhook payload Data → the transcript text or JSON from the webhook payload Connect Google Sheets OAuth2. Chat entry point and Agent Add Chat Trigger to receive user questions. Add AI Agent and connect: a Chat Model (for example OpenAI Chat Model) the Google Sheets Tool to read relevant rows In the Agent system message, instruct: Use the Sheets tool to fetch transcript rows matching the question Answer only from those rows Cite or reference row context as needed Test and activate Upload a sample video to the watched Drive folder. Wait for the callback to populate your sheet. Ask a question through the Chat Trigger and confirm the agent quotes only from the retrieved rows. Activate your template and let it automate the task. How to take this further Team memory:** Ask “What did we decide on pricing last week?” and get the exact clip and answer. Study helper:** Drop classes in, then ask for key points or formulas by topic. Customer FAQ builder:** Turn real support calls into answers your team can reuse. Podcast highlights:** Find quotes, tips, and standout moments from each episode. Meeting catch-up:** Get decisions and action items from any recording, fast. Marketing snippets:** Pull short, social-ready lines from long demos or webinars. Team learning hub:** Grow a searchable video brain that remembers everything. This workflow uses the VLM Run node for scalable, async video transcription and the AI Agent for grounded Q&A from Sheets, giving you a durable pipeline from upload to searchable answers with minimal upkeep.

This n8n template automates the collection and enrichment of Product Hunt posts using AI and Google Sheets. It fetches new tools daily, translates content, categorizes them intelligently, and saves everything into a structured spreadsheet—ideal for building directories, research dashboards, newsletters, or competitive intelligence assets. Good to know Sticky notes inside the workflow explain each functional block and required configurations. Uses cursor-based pagination to safely fetch Product Hunt data. AI agent handles translation, documentation generation, tech extraction, and function area classification. Category translations are synced with a Google Sheets dictionary to avoid duplicates. All enriched entries are stored in a clean “Tools” sheet for easy filtering or reporting. How it works A schedule trigger starts the workflow daily. Product Hunt posts are retrieved via GraphQL and processed in batches. A code node restructures each product into a consistent schema. The workflow checks if a product already exists in Google Sheets. For new items, the AI agent generates metadata, translations, and documentation. Categories are matched or added to a Google Sheets dictionary. The final enriched product entry is appended or updated in the spreadsheet. Pagination continues until no next page remains. How to use Connect Product Hunt OAuth2, Google Sheets, and OpenAI credentials. Adjust the schedule trigger to your preferred frequency. Optionally expand enrichment fields (tags, scoring, custom classifications). Replace the trigger with a webhook or manual trigger if needed. Requirements Product Hunt OAuth2 credentials Google Sheets account OpenAI (or compatible) API access Customising this workflow Add Slack or Discord notifications for new tools. Push enriched data to Airtable, Notion, or a database. Extend AI enrichment with summaries or SEO fields. Use the Google Sheet as a backend for dashboards or frontend applications.

Description Automatically extract a structured skill matrix from PDF resumes in a Google Drive folder and store results in Google Sheets. Uses Azure OpenAI (GPT-4o-mini) to analyze predefined tech stacks and filters for relevant proficiency. Fast, consistent insights ready for review. 🔍📊 What This Template Does Fetches all resumes from a designated Google Drive folder (“Resume_store”). 🗂️ Downloads each resume file securely via Google Drive API. ⬇️ Extracts text from PDF files for analysis. 📄➡️📝 Analyzes skills with Azure OpenAI (GPT-4o-mini), rating 1–5 and estimating years. 🤖 Parses and filters to include only skills with proficiency > 2, then updates Google Sheets (“Resume store” → “Sheet2”). ✅ Key Benefits Saves hours on manual resume screening. ⏱️ Produces a consistent, structured skill matrix. 📐 Focuses on intermediate to expert skills for faster shortlisting. 🎯 Centralizes candidate data in Google Sheets for easy sharing. 🗃️ Features Predefined tech stack focus: React, Node.js, Angular, Python, Java, SQL, Docker, Kubernetes, AWS, Azure, GCP, HTML, CSS, JavaScript. 🧰 Proficiency scoring (1–5) and estimated years of experience. 📈 PDF-to-text extraction for robust parsing. 🧾 JSON parsing with error handling for invalid outputs. 🛡️ Manual Trigger to run on demand. ▶️ Requirements n8n instance (cloud or self-hosted). Google Drive access with credentials to the “Resume_store” folder. Google Sheets access to the “Resume store” spreadsheet and “Sheet2” tab. Azure OpenAI with GPT-4o-mini deployed and connected via secure credentials. PDF text extraction enabled within n8n. Target Audience HR and Talent Acquisition teams. 👥 Recruiters and staffing agencies. 🧑‍💼 Operations teams managing hiring pipelines. 🧭 Tech hiring managers seeking consistent skill insights. 💡 Step-by-Step Setup Instructions Place candidate resumes (PDF) into Google Drive → “Resume_store”. In n8n, add Google Drive and Google Sheets credentials and authorize access. In n8n, add Azure OpenAI credentials (GPT-4o-mini deployment). Import the workflow, assign credentials to each node, and confirm folder/sheet names. Run the Manual Trigger to execute the flow and verify data in “Resume store” → “Sheet2”.

Try It Out! The AI Investment Research Assistant (Discord Summary Bot) transforms your Discord server into a professional-grade AI-driven crypto intelligence center. Running automatically every morning, it gathers real-time news, sentiment, and market data from multiple trusted sources — including NewsAPI, Crypto Compare, and CoinGecko — covering the most influential digital assets like BTC, ETH, SOL, BNB, and ADA. An AI Research Analyst Agent then processes this data using advanced reasoning and summarization to deliver a structured Market Intelligence Briefing. Each report distills key market events, sentiment shifts, price movements, and analyst-grade insights, all formatted into a visually clean and actionable message that posts directly to your Discord channel. Whether you’re a fund manager, community owner, or analyst, this workflow helps you stay informed about market drivers — without manually browsing dozens of news sites or data dashboards. Detailed Use Cases Crypto Research Teams:** Automate daily market briefings across key assets. Investment Communities:** Provide daily insights and sentiment overviews directly on Discord. Trading Desks:** Quickly review summarized market shifts and performance leaders. DAOs or Fund Analysts:** Centralize institutional-style crypto intelligence into your server. How It Works Daily Trigger (Schedule Node) – Activates each morning to begin data collection. News Aggregation Layer – Uses NewsAPI (and optionally CryptoPanic or GDELT) to fetch the latest crypto headlines and event coverage. Market & Sentiment Fetch – Collects market metrics via CoinGecko or Crypto Compare, including: 24-hour price change Market cap trend Social sentiment or Fear & Greed index AI Research Analyst (LLM Agent) – Processes and synthesizes all data into a cohesive insight report containing: 🧠 Executive Summary 📊 Top Gainers & Losers 💬 Sentiment Overview 🔍 Analyst Take / Actionable Insight Formatting Layer (Code Node) – Converts the analysis into a Discord-ready structure. Discord Posting Node – Publishes the final Market Intelligence Briefing to a specified Discord channel. Setup and Customization Import this workflow into your n8n workspace. Configure credentials: NewsAPI Key – For crypto and blockchain news. CoinGecko / Crypto Compare API Key – For real-time asset data. LLM Credential – OpenAI, Gemini, or Anthropic. Discord Webhook URL or Bot Token – To post updates. Customize the tracked assets in the News and Market nodes (BTC, ETH, SOL, BNB, ADA, etc.). Set local timezone for report delivery. Deploy and activate — your server will receive automated morning briefings. Output Format Each daily report includes: 📰 AI Market Intelligence Briefing 📅 Date: October 16, 2025 💰 Top Movers: BTC +2.3%, SOL +1.9%, ETH -0.8% 💬 Sentiment: Moderately Bullish 🔍 Analyst Take: Accumulation signals forming in mid-cap layer-1s. 📈 Outlook: Positive bias, with ETH showing strong support near $2,400. Compact yet rich in insight, this format ensures quick readability and fast decision-making for traders and investors. (Optional) Extend This Workflow Portfolio-Specific Insights:** Fetch your wallet holdings from AFK Crypto or Zapper APIs for personalized reports. Interactive Commands:** Add /compare or /analyze commands for Discord users. Multi-Language Summaries:** Auto-translate for international communities. Historical Data Logging:** Store briefings in Notion or Google Sheets. Weekly Recaps:** Summarize all daily reports into a long-form analysis. Requirements n8n Instance** (with HTTP Request, AI Agent, and Discord nodes enabled) NewsAPI Key** CoinGecko / Crypto Compare API Key** LLM Credential** (OpenAI / Gemini / Anthropic) Discord Bot Token or Webhook URL** APIs Used GET https://newsapi.org/v2/everything?q=crypto OR bitcoin OR ethereum OR defi OR nft&language=en&sortBy=publishedAt&pageSize=10 GET https://api.coingecko.com/api/v3/simple/price?ids=bitcoin,ethereum,solana&vs_currencies=usd&include_market_cap=true&include_24hr_change=true (Optional) GET https://cryptopanic.com/api/v1/posts/?auth_token=YOUR_TOKEN&kind=news (Optional) GET https://api.gdeltproject.org/api/v2/doc/doc?query=crypto&format=json Summary The AI Investment Research Assistant (Discord Summary Bot) is your personal AI research analyst — delivering concise, data-backed crypto briefings directly to Discord. It intelligently combines news aggregation, sentiment analysis, and AI reasoning to create actionable market intelligence each morning. Ideal for crypto traders, funds, or educational communities seeking a reliable daily edge — this workflow replaces hours of manual research with one automated, professional-grade summary. Our Website: https://afkcrypto.com/ Check our blogs: https://www.afkcrypto.com/blog

Meet Troy, your intelligent personal assistant that seamlessly manages your Google Calendar and Tasks through Telegram. This workflow combines AI-powered natural language processing with MCP (Model Context Protocol) integration to provide a conversational interface for scheduling meetings, managing tasks, and organizing your digital life. Key Features 📅 Smart Calendar Management Create single and recurring events with conflict detection Support for multiple attendees (1-2 attendee variants) Automatic time zone handling (Bangladesh Standard Time) Weekly recurring event scheduling Event retrieval, updates, and deletion ✅ Task Management Create, update, and delete tasks in Google Tasks Mark tasks as completed Retrieve task lists with completion status Task repositioning and organization Parent-child task relationships 🤖Intelligent Processing Natural language understanding for scheduling requests Automatic conflict detection before event creation Context-aware responses with conversation memory Error handling with fallback messages 📱 Telegram Interface Real-time chat interaction Simple commands and natural language Instant confirmations and updates Error notifications Workflow Components Core Architecture: Telegram Trigger for user messages AI Agent with GPT-4o-mini processing MCP Client Tools for Google services Conversation memory for context Error handling with backup responses MCP Integrations: Google Calendar MCP Server (6 specialized tools) Google Tasks MCP Server (5 task operations) Custom HTTP tool for advanced task positioning Use Cases Calendar Scenarios: "Schedule a meeting tomorrow at 3 PM with john@example.com" "Set up weekly team standup every Monday at 10 AM" "Check my calendar for conflicts this afternoon" "Delete the meeting with ID xyz123" Task Management: "Add a task to buy groceries" "Mark the project report task as completed" "Update my presentation task due date to Friday" "Show me all pending tasks" Setup Requirements Required Credentials: Google Calendar OAuth2 Google Tasks OAuth2 OpenAI API key Telegram Bot token ** MCP Configuration:** Two MCP server endpoints for Google services Proper webhook configurations SSL-enabled n8n instance for MCP triggers Business Benefits Productivity: Voice-to-action task and calendar management *Efficiency: *Eliminate app switching with chat interface Intelligence: AI prevents scheduling conflicts automatically Accessibility: Simple Telegram commands for complex operations Technical Specifications Components: 1 Telegram trigger 1 AI Agent with memory 2 MCP triggers (Calendar & Tasks) 13 Google service tools Error handling flows Response Time: Sub-second for most operations *Memory: *Session-based conversation context Timezone: Automatic Bangladesh Standard Time conversion This personal assistant transforms how you interact with Google services, making scheduling and task management as simple as sending a text message to Troy on Telegram. Tags: personal-assistant, mcp-integration, google-calendar, google-tasks, telegram-bot, ai-agent, productivity

🧠 Google Ads Monthly Performance Optimization (Channable + Google Ads + Relevance AI) 🚀 Overview This workflow automatically analyzes your Google Ads performance every month, identifies top-performing themes and categories, and regenerates optimized ad copy using Relevance AI — powered by insights from your Channable product feed. It then saves the improved ads to Google Sheets for review and sends a detailed performance report to your Slack workspace. Ideal for marketing teams who want to automate ad optimization at scale with zero manual intervention. 🔗 Integrations Used Google Ads** → Fetch campaign and ad performance metrics using GAQL. Relevance AI** → Analyze performance data and regenerate ad copy using AI agents and tools. Channable** → Pull updated product feeds for ad refresh cycles. Google Sheets** → Save optimized ad copy for review and documentation. Slack** → Send a 30-day performance report to your marketing team. 🧩 Workflow Summary | Step | Node | Description | | ---- | --------------------------------------------------- | --------------------------------------------------------------------------- | | 1 | Monthly Schedule Trigger | Runs automatically on the 1st of each month to review last 30 days of data. | | 2 | Get Google Ads Performance Data | Fetches ad metrics via GAQL query (impressions, clicks, CTR, etc.). | | 3 | Calculate Performance Metrics | Groups results by ad group and theme to find top/bottom performers. | | 4 | AI Performance Analysis (Relevance AI) | Generates human-readable insights and improvement suggestions. | | 5 | Update Knowledge Base (Relevance AI) | Saves new insights for future ad copy training. | | 6 | Get Updated Product Feed (Channable) | Retrieves the latest catalog items for ad regeneration. | | 7 | Split Into Batches | Splits the feed into groups of 50 to avoid API rate limits. | | 8 | Regenerate Ad Copy with Insights (Relevance AI) | Rewrites ad copy with the latest product and performance data. | | 9 | Save Optimized Ads to Sheets | Writes output to your “Optimized Ads” Google Sheet. | | 10 | Generate Performance Report | Summarizes the AI analysis, CTR trends, and key insights. | | 11 | Email Performance Report (Slack) | Sends report directly to your Slack channel/team. | 🧰 Requirements Before running the workflow, make sure you have: A Google Ads account with API access and OAuth2 credentials. A Relevance AI project (with one Agent and one Tool setup). A Channable account with API key and project feed. A Google Sheets document for saving results. A Slack webhook URL for sending performance summaries. ⚙️ Environment Variables Add these environment variables to your n8n instance (via .env or UI): | Variable | Description | | -------------------------------- | ------------------------------------------------------------------- | | GOOGLE_ADS_API_VERSION | API version (e.g., v17). | | GOOGLE_ADS_CUSTOMER_ID | Your Google Ads customer ID. | | RELEVANCE_AI_API_URL | Base Relevance AI API URL (e.g., https://api.relevanceai.com/v1). | | RELEVANCE_AGENT_PERFORMANCE_ID | ID of your Relevance AI Agent for performance analysis. | | RELEVANCE_KNOWLEDGE_SOURCE_ID | Knowledge base or dataset ID used to store insights. | | RELEVANCE_TOOL_AD_COPY_ID | Relevance AI tool ID for generating ad copy. | | CHANNABLE_API_URL | Channable API endpoint (e.g., https://api.channable.com/v1). | | CHANNABLE_COMPANY_ID | Your Channable company ID. | | CHANNABLE_PROJECT_ID | Your Channable project ID. | | FEED_ID | The feed ID for product data. | | GOOGLE_SHEET_ID | ID of your Google Sheet to store optimized ads. | | SLACK_WEBHOOK_URL | Slack Incoming Webhook URL for sending reports. | 🔐 Credentials Setup in n8n | Credential | Type | Usage | | ----------------------------------------------- | ------- | --------------------------------------------------- | | Google Ads OAuth2 API | OAuth2 | Authenticates your Ads API queries. | | HTTP Header Auth (Relevance AI & Channable) | Header | Uses your API key as Authorization: Bearer <key>. | | Google Sheets OAuth2 API | OAuth2 | Writes optimized ads to Sheets. | | Slack Webhook | Webhook | Sends monthly reports to your team channel. | 🧠 Example AI Insight Output { "insights": [ "Ad groups using 'vegan' and 'organic' messaging achieved +23% CTR.", "'Budget' keyword ads underperformed (-15% CTR).", "Campaigns featuring 'new' or 'bestseller' tags showed higher conversion rates." ], "recommendations": [ "Increase ad spend for top-performing 'vegan' and 'premium' categories.", "Revise copy for 'budget' and 'sale' ads with low CTR." ] } 📊 Output Example (Google Sheet) | Product | Category | Old Headline | New Headline | CTR Change | Theme | | ------------------- | -------- | ------------------------ | -------------------------------------------- | ---------- | ------- | | Organic Protein Bar | Snacks | “Healthy Energy Anytime” | “Organic Protein Bar — 100% Natural Fuel” | +12% | Organic | | Eco Face Cream | Skincare | “Gentle Hydration” | “Vegan Face Cream — Clean, Natural Moisture” | +17% | Vegan | 📤 Automation Flow Run Automatically on the first of every month (cron: 0 0 1 * *). Fetch Ads Data → Analyze & Learn → Generate New Ads → Save & Notify. Every iteration updates the AI’s knowledge base — improving your campaigns progressively. ⚡ Scalability The flow is batch-optimized (50 items per request). Works for large ad accounts with up to 10,000 ad records. AI analysis & regeneration steps are asynchronous-safe (timeouts extended). Perfect for agencies managing multiple ad accounts — simply duplicate and update the environment variables per client. 🧩 Best Use Cases Monthly ad creative optimization for eCommerce stores. Marketing automation for Google Ads campaign scaling. Continuous learning ad systems powered by Relevance AI insights. Agencies automating ad copy refresh cycles across clients. 💬 Slack Report Example 30-Day Performance Optimization Report Date: 2025-10-01 Analysis Period: Last 30 days Ads Analyzed: 842 Top Performing Themes Vegan: 5.2% CTR (34 ads) Premium: 4.9% CTR (28 ads) Underperforming Themes Budget: 1.8% CTR (12 ads) AI Insights “Vegan” and “Premium” themes outperform baseline by +22% CTR. “Budget” ads underperform due to lack of value framing. Next Optimization Cycle: 2025-11-01 🛠️ Maintenance Tips Update your GAQL query occasionally to include new metrics or segments. Refresh Relevance AI tokens every 90 days (if required). Review generated ads in Google Sheets before pushing them live. Test webhook and OAuth connections after major n8n updates. 🧩 Import Instructions Open n8n → Workflows → Import from File / JSON. Paste this workflow JSON or upload it. Add all required environment variables and credentials. Execute the first run manually to validate connections. Once verified, enable scheduling for automatic monthly runs. 🧾 Credits Developed for AI-driven marketing teams leveraging Google Ads, Channable, and Relevance AI to achieve continuous ad improvement — fully automated via n8n.